PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?item ?itemLabel ?itemCoord ?itemCountry ?itemCountryLabel ?desCountry ?desCountryLabel WHERE {
  {
    SELECT ?item ( COUNT( DISTINCT ?desCountry ) AS ?cnt ) WHERE {
      ?item wdt:P1435 ?des .
      ?item wdt:P17 ?itemCountry .
      ?des wdt:P17 ?desCountry .
      FILTER ( ?itemCountry != ?desCountry )
    }
    GROUP BY ?item
    HAVING ( ?cnt > 1 )
  }
  ?item wdt:P17 ?itemCountry .
  ?item wdt:P1435 ?des .
  ?des wdt:P17 ?desCountry .
  FILTER ( ?itemCountry != ?desCountry ) OPTIONAL {
    ?item wdt:P625 ?itemCoord .
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
  OPTIONAL {
    ?itemCountry rdfs:label ?itemCountryLabel FILTER ( LANG( ?itemCountryLabel ) = "en" )
  }
  OPTIONAL {
    ?desCountry rdfs:label ?desCountryLabel FILTER ( LANG( ?desCountryLabel ) = "en" )
  }
}
ORDER BY ?itemLabel ?itemCountryLabel ?desCountryLabel

I executed the query on Wikidata. It returns items that have heritage designations (P1435) from countries different from the country they are located in, counting only items that have more than one distinct such designation country. The query returns the item IRI and English label (when available), item coordinates (P625) if available, the item's country IRI and English label, and each distinct heritage-designation country IRI and English label. Results are ordered by item label, item country label, and heritage designation country label. The query returned 1,129 rows (multiple rows per item for each designation country). Example rows include (item, itemLabel, itemCountryLabel, desCountryLabel):
- wd:Q96211973, "Zhukovsky St., 20 / Samokisha St., 11", "Soviet Union", "Russia"
- wd:Q96211973, "Zhukovsky St., 20 / Samokisha St., 11", "Soviet Union", "Ukraine"
- wd:Q4155917, "Дворец графини Паниной", "Russia", "Ukraine"
- wd:Q4155917, "Дворец графини Паниной", "Ukraine", "Russia"

You can run the provided SPARQL query directly against the Wikidata endpoint to retrieve the full set of results.

Which items have a heritage designation from a country different from the country they are located in, and have more than one such designation? Please include their labels, the labels of their countries, the labels of the countries of their heritage designations, and their coordinates if available. Order results by item label, country label, and heritage designation country label.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which items have a heritage designation from a country different from the country they are located in, and have more than one such designation? Please include their labels, the labels of their countries, the labels of the countries of their heritage designations, and their coordinates if available. Order results by item label, country label, and heritage designation country label.

[Assistant] I will search for the property used for "heritage designation" in Wikidata and then look for items with that property and country (located in country) to find those where the designation's country differs from the located country. I'll explain each step and run queries to discover relevant properties and verify identifiers.

[Tool]
Top 10 property alternatives:
1. heritage designation, also known as protection, protected status, listing, listed status, legal protection (wd:P1435 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): heritage designation of a cultural or natural site, subproperty of has part(s), subproperty of instance of
2. appears in the heritage monument list (wd:P2817 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): heritage monument is a part of the list of heritage monuments
3. dedicated heritage entity, also known as associated heritage entity, has museum (wd:P8786 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): heritage entity dedicated to or associated with the item's subject
4. World Heritage criteria, also known as WHS criteria (wd:P2614 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): selection criteria for UNESCO's cultural and natural 'World Heritage' designation since 2005
5. National Heritage List for England number, also known as EH list number, English Heritage list number, HE list number, Historic England list number, listed building number, England (wd:P1216 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): number on the National Heritage List for England
6. World Heritage Tentative List ID (wd:P4171 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for a site on the UNESCO World Heritage Tentative Lists
7. significant place, also known as place associated with the subject, sign. place, significant location, significant landmark, notable place (wd:P7153 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): significant or notable places associated with the subject, subproperty of location
8. intangible cultural heritage status (wd:P3259 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): status of an item that is designated as intangible heritage
9. FOIH heritage types ID, also known as Flemish organization for Immovable Heritage heritage types ID, Onroerend Erfgoed heritage types ID (wd:P4307 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for a heritage type in the thesaurus of the Flemish organization for Immovable Heritage
10. NRHP reference number, also known as National Register of Historic Places ID, National Register of Historic Places number, National Register of Historic Places reference number, NRHP, NRHP ID (wd:P649 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier in the National Register of Historic Places assigned by the National Park Service of the USA

[Assistant] I'll list some triples using the property wdt:P1435 (heritage designation) to see typical values and how the designation indicates the country (e.g., whether the designation item has a 'country' property).

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                                      | property                         | object                                              |
| ------------------------------------------------------------ | -------------------------------- | --------------------------------------------------- |
| monastery of Skellig Michael (wd:Q105159796)                 | heritage designation (wdt:P1435) | UNESCO (wd:Q7809)                                   |
| St. Peter's Lutheran Church (New York, N.Y.) (wd:Q107641696) | heritage designation (wdt:P1435) | church building (wd:Q16970)                         |
| Babylon (wd:Q100329356)                                      | heritage designation (wdt:P1435) | World Heritage Site (wd:Q9259)                      |
| wd:Q105761452                                                | heritage designation (wdt:P1435) | Bronze Age (wd:Q11761)                              |
| Colosseum (wd:Q10285)                                        | heritage designation (wdt:P1435) | Italian national heritage (wd:Q26971668)            |
| wd:Q106294439                                                | heritage designation (wdt:P1435) | paleontology (wd:Q7205)                             |
| wd:Q102270161                                                | heritage designation (wdt:P1435) | monument (wd:Q4989906)                              |
| Godbns Church (wd:Q107637090)                                | heritage designation (wdt:P1435) | statue (wd:Q179700)                                 |
| Biel/Bienne (wd:Q1034)                                       | heritage designation (wdt:P1435) | Swiss townscape worthy of protection (wd:Q12127133) |
| Koper (wd:Q1015)                                             | heritage designation (wdt:P1435) | monument of local significance (wd:Q18363639)       |
| ...                                                          | ...                              | ...                                                 |

[Assistant]
I'll run a SPARQL query that:
- finds items with heritage designations (P1435) whose designation items have a country (P17) different from the item's country (P17),
- selects items that have more than one such designation (counting distinct designation items),
- then returns for those items the item IRI, item label, coordinates, the item's country IRI and label, and the designation country IRIs and labels,
ordered as requested.

I'll execute a query with a subselect to first find items with COUNT(DISTINCT ?des) > 1, then retrieve the designation countries for those items. Now I will execute the query.

[Tool]
Got 1,495 rows and 7 columns, showing the first 5 and last 5 rows below:
| item                                                 | itemLabel                                  | itemCoord                                   | itemCountry                    | itemCountryLabel      | desCountry        | desCountryLabel |
| ---------------------------------------------------- | ------------------------------------------ | ------------------------------------------- | ------------------------------ | --------------------- | ----------------- | --------------- |
| wd:Q125510803                                        |                                            | POINT(20.253917 53.180472) (geo:wktLiteral) | Duchy of Masovia (wd:Q2361927) | Duchy of Masovia (en) | Poland (wd:Q36)   | Poland (en)     |
| wd:Q125510803                                        |                                            | POINT(20.253917 53.180472) (geo:wktLiteral) | Duchy of Masovia (wd:Q2361927) | Duchy of Masovia (en) | Poland (wd:Q36)   | Poland (en)     |
| wd:Q129810234                                        |                                            |                                             | Empire of Japan (wd:Q188712)   | Empire of Japan (en)  | Taiwan (wd:Q865)  | Taiwan (en)     |
| wd:Q129810234                                        |                                            |                                             | Empire of Japan (wd:Q188712)   | Empire of Japan (en)  | Taiwan (wd:Q865)  | Taiwan (en)     |
| wd:Q3583373                                          |                                            | POINT(21.074200 42.238000) (geo:wktLiteral) | Kosovo (wd:Q1246)              | Kosovo (en)           | Serbia (wd:Q403)  | Serbia (en)     |
| ...                                                  | ...                                        | ...                                         | ...                            | ...                   | ...               | ...             |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (en) | POINT(34.092778 44.948889) (geo:wktLiteral) | Soviet Union (wd:Q15180)       | Soviet Union (en)     | Ukraine (wd:Q212) | Ukraine (en)    |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (en) | POINT(34.092778 44.948889) (geo:wktLiteral) | Ukraine (wd:Q212)              | Ukraine (en)          | Russia (wd:Q159)  | Russia (en)     |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (en)                | POINT(34.098600 44.435200) (geo:wktLiteral) | Russia (wd:Q159)               | Russia (en)           | Ukraine (wd:Q212) | Ukraine (en)    |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (en)                | POINT(34.098600 44.435200) (geo:wktLiteral) | Russia (wd:Q159)               | Russia (en)           | Ukraine (wd:Q212) | Ukraine (en)    |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (en)                | POINT(34.098600 44.435200) (geo:wktLiteral) | Ukraine (wd:Q212)              | Ukraine (en)          | Russia (wd:Q159)  | Russia (en)     |

[Assistant] Now I'll run a refined SPARQL query that counts distinct heritage-designation countries (desCountry) per item and selects those with more than one distinct foreign designation country. This makes sure an item has heritage designations coming from more than one country different from the country it is located in. I'll request item and country IRIs, labels in English, and coordinates when available.

[Tool]
Got 1,129 rows and 7 columns, showing the first 5 and last 5 rows below:
| item                                                 | itemLabel                                  | itemCoord                                   | itemCountry              | itemCountryLabel  | desCountry        | desCountryLabel |
| ---------------------------------------------------- | ------------------------------------------ | ------------------------------------------- | ------------------------ | ----------------- | ----------------- | --------------- |
| wd:Q20438365                                         |                                            | POINT(20.753600 42.561000) (geo:wktLiteral) | Kosovo (wd:Q1246)        | Kosovo (en)       | Serbia (wd:Q403)  | Serbia (en)     |
| wd:Q2402336                                          |                                            | POINT(20.669700 42.375200) (geo:wktLiteral) | Kosovo (wd:Q1246)        | Kosovo (en)       | Serbia (wd:Q403)  | Serbia (en)     |
| wd:Q3583429                                          |                                            | POINT(20.715900 42.587900) (geo:wktLiteral) | Kosovo (wd:Q1246)        | Kosovo (en)       | Serbia (wd:Q403)  | Serbia (en)     |
| wd:Q3581599                                          |                                            | POINT(20.845000 42.158900) (geo:wktLiteral) | Kosovo (wd:Q1246)        | Kosovo (en)       | Serbia (wd:Q403)  | Serbia (en)     |
| wd:Q3320281                                          |                                            | POINT(20.704600 42.603100) (geo:wktLiteral) | Kosovo (wd:Q1246)        | Kosovo (en)       | Serbia (wd:Q403)  | Serbia (en)     |
| ...                                                  | ...                                        | ...                                         | ...                      | ...               | ...               | ...             |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (en) | POINT(34.092778 44.948889) (geo:wktLiteral) | Soviet Union (wd:Q15180) | Soviet Union (en) | Russia (wd:Q159)  | Russia (en)     |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (en) | POINT(34.092778 44.948889) (geo:wktLiteral) | Soviet Union (wd:Q15180) | Soviet Union (en) | Ukraine (wd:Q212) | Ukraine (en)    |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (en) | POINT(34.092778 44.948889) (geo:wktLiteral) | Ukraine (wd:Q212)        | Ukraine (en)      | Russia (wd:Q159)  | Russia (en)     |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (en)                | POINT(34.098600 44.435200) (geo:wktLiteral) | Russia (wd:Q159)         | Russia (en)       | Ukraine (wd:Q212) | Ukraine (en)    |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (en)                | POINT(34.098600 44.435200) (geo:wktLiteral) | Ukraine (wd:Q212)        | Ukraine (en)      | Russia (wd:Q159)  | Russia (en)     |

[Assistant]
The results include historical countries like 'Soviet Union' as the located country; those could be legitimate per the data. The query seems to work.

I'll now prepare the final SPARQL query to return the requested fields and ensure we include labels for items, countries, and designation countries, and coordinates when available. The query I already used fits the requirements: it finds items with more than one heritage designation coming from countries different from their located country, and returns the requested fields, ordered by item label, item country label, and designation country label.

I'll provide the final query and the summary of results (note: per the instructions I must execute the final query before answering—I've executed it). I'll now return the final SPARQL query and describe the answer (since the result set is large, I'll state how many rows and give an example or note that results were returned).

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?personLabel ?dod WHERE {
  ?person wdt:P31 wd:Q5 .
  ?person wdt:P570 ?dod .
  FILTER ( ?dod >= "2021-01-01T00:00:00Z" ^^ xsd:dateTime && ?dod <= "2021-01-31T23:59:59Z" ^^ xsd:dateTime ) OPTIONAL {
    ?person rdfs:label ?personLabel .
    FILTER ( LANG( ?personLabel ) = "en" )
  }
}
ORDER BY ?dod ?person
LIMIT 500

I executed the query above against Wikidata. It returned 500 results (persons who are instances of human with a date of death in January 2021), ordered by date of death and by item identifier.

Example rows from the result (first 5 shown by the endpoint):
- wd:Q100146456 — "José Ramón Ávalos Navarrete" — 2021-01-01T00:00:00Z
- wd:Q100239938 — "James Paul Kocsis" — 2021-01-01T00:00:00Z
- wd:Q100303070 — "Robert C. Della Rocca" — 2021-01-01T00:00:00Z
- wd:Q100531686 — "Harold Franklin" — 2021-01-01T00:00:00Z
- wd:Q100548125 — "Anwar Hossain (Industrialist)" — 2021-01-01T00:00:00Z

(And the endpoint returned 500 total rows; the query is limited to 500 results.)

What are the names and dates of death of humans who died between January 1, 2021, and January 31, 2021, ordered by their date of death and name and limited to 500 results?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the names and dates of death of humans who died between January 1, 2021, and January 31, 2021, ordered by their date of death and name and limited to 500 results?

[Assistant] Step 1 — I'll search for the property for "date of death" and for the entity "human" in Wikidata so I can use the correct property and item identifiers in the query. I'll first search for the property "date of death".

[Tool]
Top 10 property alternatives:
1. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): subproperty of dissolved, abolished or demolished date, date on which the subject died, subproperty of end time
2. place of death, also known as POD, location of death, killed in, died in, died (wd:P20 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, subproperty of location
3. date of birth, also known as year of birth, DOB, born on, birthyear, born (wd:P569 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): date on which the subject was born, subproperty of inception
4. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): date on which the person was buried or cremated soon after death, subproperty of point in time
5. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): total (cumulative) number of people who died since start as a direct result of an event or cause
6. birthday, also known as birth day, b-day, bday (wd:P3150 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., subproperty of date of birth
7. commemorates, also known as anniversary of, monument to, memorial to, memorializes, marks (wd:P547 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): what the place, monument, memorial, or holiday, commemorates, subproperty of main subject
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. inception, also known as inception date, founding date, founded in, founded on date, founded on (wd:P571 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): time when an entity begins to exist; for date of official opening use P1619, subproperty of start time
10. dissolved, abolished or demolished date, also known as end date, publication end date, ended, final issue, final year (wd:P576 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, subproperty of end time

[Assistant] Step 2 — I'll verify the Wikidata item for "human" to make sure I use the correct identifier (expected wd:Q5). Then I'll build and run a SPARQL query that finds items that are instance of human (P31 = Q5) with a date of death (P570) in January 2021. I'll explain the query before executing it. Now I'll search for the entity "human".

[Tool]
Top 10 entity alternatives:
1. human, also known as nonfictional human, non-fictional human, modern humans, people, person (wd:Q5)
2. Homo sapiens, also known as humans, men, man, human beings, human being (wd:Q15978631): species of mammal, instance of taxon
3. Uman, also known as Humań (wd:Q208499): instance of city of regional significance of Ukraine, city in Cherkasy Oblast in central Ukraine
4. Human (wd:Q849189): 1991 album by Death, instance of album
5. Human (wd:Q919463): 2008 song by The Killers, instance of single, instance of song
6. Human Entertainment, also known as Human, Human Corporation (wd:Q2408214): Japanese video game developer and publisher, instance of video game developer
7. Human (wd:Q20629223): 2015 film by Yann Arthus-Bertrand, instance of film
8. Human (wd:Q27921626): 2016 song by Rag'n'Bone Man, instance of single, instance of song
9. Human (wd:Q735359): 2008 studio album by Brandy, instance of album
10. Human (wd:Q1145446): original song written and composed by Jimmy Jam and Terry Lewis; first recorded by The Human League, instance of musical work/composition

[Assistant] I'll construct a SPARQL SELECT query that returns items ?person with date of death ?dod. It will filter ?dod to between 2021-01-01 and 2021-01-31 inclusive. The results will be ordered by ?dod and ?person and limited to 500. I will also retrieve rdfs:label in English where available as OPTIONAL. Now I'll run the query.

[Tool]
Got 500 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                                        | personLabel                        | dod                                 |
| --------------------------------------------- | ---------------------------------- | ----------------------------------- |
| José Ramón Ávalos Navarrete (wd:Q100146456)   | José Ramón Ávalos Navarrete (en)   | 2021-01-01T00:00:00Z (xsd:dateTime) |
| James Paul Kocsis (wd:Q100239938)             | James Paul Kocsis (en)             | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Robert C. Della Rocca (wd:Q100303070)         | Robert C. Della Rocca (en)         | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Harold Franklin (wd:Q100531686)               | Harold Franklin (en)               | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Anwar Hossain (Industrialist) (wd:Q100548125) | Anwar Hossain (Industrialist) (en) | 2021-01-01T00:00:00Z (xsd:dateTime) |
| ...                                           | ...                                | ...                                 |
| Rajalakshmi Jayaram (wd:Q110323021)           | Rajalakshmi Jayaram (en)           | 2021-01-01T00:00:00Z (xsd:dateTime) |
| wd:Q110337819                                 |                                    | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Robert Preston (wd:Q110343842)                | Robert Preston (en)                | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Dewa Mavhinga (wd:Q110376833)                 | Dewa Mavhinga (en)                 | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Qi An (wd:Q110406649)                         | Qi An (en)                         | 2021-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
Before calling the property search, I planned to find the Wikidata property for "date of death" so I can filter by it (expected P570). Then I called search_property with "date of death". After that call I verified the property identifier.

Before calling the entity search, I planned to find the Wikidata item for "human" (expected Q5). Then I called search_entity with "human" and verified the identifier.

Next I constructed a SPARQL SELECT query that:
- selects items ?person with instance of human (wdt:P31 wd:Q5)
- has a date of death ?dod (wdt:P570)
- filters ?dod between 2021-01-01T00:00:00Z and 2021-01-31T23:59:59Z inclusive
- optionally fetches rdfs:label in English
- orders by ?dod and ?person
- limits results to 500

I executed that query to make sure it returns the expected results.

Below is the final SPARQL query I executed and the summary of results.

Now I will provide the final answer.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?guest ( COUNT( DISTINCT ?episode ) AS ?appearances ) WHERE {
  ?episode wdt:P179 wd:Q565894 .
  ?episode wdt:P5030 ?guest .
}
GROUP BY ?guest
ORDER BY DESC ( ?appearances )

Got 333 rows and 2 columns, showing the first 5 and last 5 rows below:
| guest                                | appearances  |
| ------------------------------------ | ------------ |
| Norbert Röttgen (wd:Q61903)          | 16 (xsd:int) |
| Olaf Scholz (wd:Q61053)              | 13 (xsd:int) |
| Peter Altmaier (wd:Q65539)           | 12 (xsd:int) |
| Sahra Wagenknecht (wd:Q77193)        | 11 (xsd:int) |
| Annalena Baerbock (wd:Q564328)       | 11 (xsd:int) |
| ...                                  | ...          |
| Viviane Reding (wd:Q235866)          | 1 (xsd:int)  |
| Susanne Hennig-Wellsow (wd:Q2369250) | 1 (xsd:int)  |
| Georg Pazderski (wd:Q24189103)       | 1 (xsd:int)  |
| Ulrich Ladurner (wd:Q24203373)       | 1 (xsd:int)  |
| Tina Hassel (wd:Q2435478)            | 1 (xsd:int)  |

Process and queries run (brief):
1) I searched for the Wikidata item for the German political talk show “Anne Will” and found wd:Q565894.
2) I inspected an example episode to confirm the property used for guests: episodes use wdt:P5030 (talk show guest) and episodes are linked to the series with wdt:P179 (part of the series).
3) I executed the SPARQL query above which counts distinct episodes (?episode) per guest (?guest) for episodes where ?episode wdt:P179 wd:Q565894 and ?episode wdt:P5030 ?guest, grouping by ?guest and ordering by DESC count.

Result summary:
- The query returns 333 distinct guests (each with the number of distinct Anne Will episodes they appeared in), ordered by number of appearances descending.
- Top results (highest numbers of appearances) include:
  - wd:Q61903 (Norbert Röttgen): 16 appearances
  - wd:Q61053 (Olaf Scholz): 13 appearances
  - wd:Q65539 (Peter Altmaier): 12 appearances
  - wd:Q77193 (Sahra Wagenknecht): 11 appearances
  - wd:Q564328 (Annalena Baerbock): 11 appearances

Notes:
- The provided SPARQL query returns the full ordered list of guests (IRIs) and their number of distinct episode appearances. If you want human-readable labels included in the results, you can add an OPTIONAL clause to fetch rdfs:label for each ?guest (filtering by language), but retrieving labels for the entire result set may cause the query to run longer or time out on this endpoint.

If you want, I can (a) return the full list of all 333 guests and counts inline here (this may be long), or (b) re-run the query including labels (and possibly with a limit or paging) to produce a labelled list. Which would you prefer?

Who are the guests who have appeared on the German political TV talk show "Anne Will," and how many distinct episodes has each guest appeared in, ordered by the number of appearances in descending order?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Who are the guests who have appeared on the German political TV talk show "Anne Will," and how many distinct episodes has each guest appeared in, ordered by the number of appearances in descending order?

[Assistant] I will first find the Wikidata item for the German TV talk show "Anne Will", then identify the property used for "guest" or "participant" on TV show episodes (likely P710 'participant' or P161 'cast member' or P710 for characters). I'll search the entity, then inspect properties used for episodes of the show and count distinct episodes per guest. I will explain each step and run intermediate queries to verify identifiers. First, I'll search for the "Anne Will" entity.

[Tool]
Top 10 entity alternatives:
1. ANNE WILL — Nach dem TV-Duell (wd:Q51466909): episode of talk show Anne Will (September 3rd, 2017) S11 E03, instance of television series episode
2. television program, also known as T. V. program, TV programme, TV program, T.V. program, T. V. show (wd:Q15416)
3. television series, also known as TV show, television show, TV-series, TV series (wd:Q5398426)
4. Show TV (wd:Q2006738): instance of television station, Turkish television station
5. Anne Will (wd:Q77772): German television journalist, television presenter, instance of human, journalist, presenter
6. TV Show (wd:Q3281229): 2007 album by Sergey Lazarev, instance of album
7. Anne Will, also known as ANNE WILL, ANNEWILL (wd:Q565894): German political TV talk show (2007–2023), instance of television program
8. reality television, also known as television reality program, television reality show, TV reality show, reality TV program, TV reality program (wd:Q182415)
9. Showtime, also known as Showtime TV, Showtime Network, Showtime Networks, Showtime (TV network), Showtime Entertainment (wd:Q23589): instance of film production company, instance of subscription television, American premium cable TV channel, instance of production company, instance of specialty channel, instance of cable channel
10. television presenter, also known as television show host, TV host, TV anchor, television host, TV presenter (wd:Q947873)

[Assistant] I'll search for items linking to the Anne Will TV show (wd:Q565894) to find how episodes are modeled (which property points to the series), so I can find episodes and their guest participants.

[Tool]
Got 297 rows and 3 columns, showing the first 10 rows below:
| subject                                                                             | property                      | object                 |
| ----------------------------------------------------------------------------------- | ----------------------------- | ---------------------- |
| Anne Will (wd:Q77772)                                                               | different from (wdt:P1889)    | Anne Will (wd:Q565894) |
| Anne Will, season 17 (wd:Q123068433)                                                | part of the series (wdt:P179) | Anne Will (wd:Q565894) |
| Carla Hinrichs (wd:Q110874465)                                                      | participant in (wdt:P1344)    | Anne Will (wd:Q565894) |
| Anne Will (wd:Q77772)                                                               | notable work (wdt:P800)       | Anne Will (wd:Q565894) |
| Caren Miosga (wd:Q122961070)                                                        | replaces (wdt:P1365)          | Anne Will (wd:Q565894) |
| s:Q83700941-95c8e700-4f51-5768-abe8-f004b1358318                                    | of (pq:P642)                  | Anne Will (wd:Q565894) |
| <https://commons.wikimedia.org/wiki/Category:Anne_Will_(talk_show)>                 | schema:about                  | Anne Will (wd:Q565894) |
| s:Q77772-d43b5fd5-4008-8438-37eb-da392222760d                                       | different from (ps:P1889)     | Anne Will (wd:Q565894) |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | part of the series (wdt:P179) | Anne Will (wd:Q565894) |
| An der „Belastungsgrenze“ – Scha...eine bessere Flüchtlingspolitik? (wd:Q123083508) | part of the series (wdt:P179) | Anne Will (wd:Q565894) |
| ...                                                                                | ...                           | ...                    |

[Assistant] I'll inspect one episode item (e.g., wd:Q123068651) to see which properties link guests/participants.

[Tool]
Got 44 rows and 3 columns, showing the first 10 rows below:
| subject                                                                             | property                      | object                                                                              |
| ----------------------------------------------------------------------------------- | ----------------------------- | ----------------------------------------------------------------------------------- |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | instance of (wdt:P31)         | season premiere (wd:Q29197)                                                         |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | title (wdt:P1476)             | Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (de)            |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | publication date (wdt:P577)   | 2023-09-10T00:00:00Z (xsd:dateTime)                                                 |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | main subject (wdt:P921)       | 2023 Bavarian state election (wd:Q60540258)                                         |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | followed by (wdt:P156)        | An der „Belastungsgrenze“ – Scha...eine bessere Flüchtlingspolitik? (wd:Q123083508) |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | part of the series (wdt:P179) | Anne Will (wd:Q565894)                                                              |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | presenter (wdt:P371)          | Anne Will (wd:Q77772)                                                               |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | talk show guest (wdt:P5030)   | Günther Beckstein (wd:Q44771)                                                       |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | IMDb ID (wdt:P345)            | tt29299098                                                                          |
| Der Fall Aiwanger – Wie groß ist...haden für die politische Kultur? (wd:Q123068651) | wdt:P31279                    | television series episode (wd:Q21191270)                                            |
| ...                                                                                | ...                           | ...                                                                                |

[Assistant] Now I'll run a SPARQL query that finds all episode items that are part of the Anne Will series (wd:Q565894), gets the talk show guest (wdt:P5030) for each episode, counts distinct episodes per guest, and returns the guest IRI, an optional label (German or English), and the count, ordered by descending count. I'll execute that query to retrieve the results.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant] The query timed out. I'll try a slightly different approach: first get all episodes of the series, then sample or count per guest in smaller batches. But better: I'll query guests and counts using wdt:P179 and wdt:P5030 but limit results to avoid timeout issues. I'll try again without retrieving labels to simplify.

[Tool]
Got 333 rows and 2 columns, showing the first 5 and last 5 rows below:
| guest                                | appearances  |
| ------------------------------------ | ------------ |
| Norbert Röttgen (wd:Q61903)          | 16 (xsd:int) |
| Olaf Scholz (wd:Q61053)              | 13 (xsd:int) |
| Peter Altmaier (wd:Q65539)           | 12 (xsd:int) |
| Sahra Wagenknecht (wd:Q77193)        | 11 (xsd:int) |
| Annalena Baerbock (wd:Q564328)       | 11 (xsd:int) |
| ...                                  | ...          |
| Viviane Reding (wd:Q235866)          | 1 (xsd:int)  |
| Susanne Hennig-Wellsow (wd:Q2369250) | 1 (xsd:int)  |
| Georg Pazderski (wd:Q24189103)       | 1 (xsd:int)  |
| Ulrich Ladurner (wd:Q24203373)       | 1 (xsd:int)  |
| Tina Hassel (wd:Q2435478)            | 1 (xsd:int)  |

[Assistant] The query returned results. Now I'll create a final query that also includes labels (preferably German then English) for the guests. I'll include OPTIONAL rdfs:label and use GROUP_CONCAT to prefer German label if present, but simpler: get labels with OPTIONAL and label may be repeated per guest; but per rules, label should be optional. I'll add SERVICE is disallowed, so I'll use OPTIONAL { ?guest rdfs:label ?guestLabel FILTER(LANG(?guestLabel) IN ('de','en')) } and then GROUP BY include ?guestLabel, but as there can be multiple labels per guest this duplicates rows. To avoid duplication, I'll use MIN(?guestLabel) with FILTER to pick one label? SPARQL MIN can choose by lexical order. But labels language preference can't be guaranteed. Simpler: fetch guest IRIs and counts; optionally add label via subquery: use subselect to get counts, then OPTIONAL join to fetch label with FILTER(LANG...). That will produce one label value if exists. I'll write final query accordingly and execute it to confirm.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item ?itemLabel ( MAX( ?date ) AS ?mostRecentPublicationDate ) WHERE {
  VALUES ?item {
    wd:Q49740
  }
  ?item wdt:P577 ?date .
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
}
GROUP BY ?item ?itemLabel

The most recent publication date for Minecraft (wd:Q49740) is 2011-11-18 (2011-11-18T00:00:00Z).

What is the most recent publication date of "Minecraft"?

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the most recent publication date of "Minecraft"?

[Assistant] I'll first search Wikidata for the entity corresponding to "Minecraft" to get its Q-id. Then I'll look up its publication/release date properties (likely P577). I'll run a query to return all publication dates for that item and select the most recent one. I'll start by searching for the entity "Minecraft".

[Tool]
Top 10 entity alternatives:
1. Minecraft (wd:Q49740): instance of esports discipline, instance of video game, 2011 video game
2. A Minecraft Movie, also known as Minecraft: The Movie, Minecraft Movie, Minecraft (wd:Q40083273): 2025 film directed by Jared Hess, instance of film
3. Minecraft, also known as Minecraft (franchise), Minecraft franchise (wd:Q25445348): instance of media franchise, media franchise
4. Minecraft: The Unlikely Tale of ...the Game That Changed Everything, also known as Minecraft (wd:Q20926210): instance of literary work, American non-fiction book
5. Minecraft, also known as calm1.ogg (wd:Q125765048): instance of musical work/composition, song by C418
6. Minecraft, also known as Minecraft Animated Series, Untitled Minecraft animated series (wd:Q126199422): instance of animated television series, upcoming animated series
7. Minecraft: Java Edition, also known as Minecraft: JE, Java Edition, Minecraft Java Edition, Minecraft Java, Minecraft (wd:Q105729297): 2011 sandbox game developed by Mojang, instance of video game
8. Minecraft (wd:Q112863331): instance of video game series, video game series
9. Minecraft (wd:Q125765049): instrumental track by C418; 2011 studio recording, instance of music track without lyrics
10. Minecraft Dungeons, also known as Minecraft: Dungeons (wd:Q56884780): 2020 video game developed by Mojang and Double Eleven, instance of video game

[Assistant] I'll look up the statements for wd:Q49740 (Minecraft) to find publication/release date properties (like P577).

[Tool]
Got 1,601 rows and 3 columns, showing the first 10 rows below:
| subject               | property                     | object                                            |
| --------------------- | ---------------------------- | ------------------------------------------------- |
| Minecraft (wd:Q49740) | instance of (wdt:P31)        | video game (wd:Q7889)                             |
| Minecraft (wd:Q49740) | title (wdt:P1476)            | Minecraft (en)                                    |
| Minecraft (wd:Q49740) | publication date (wdt:P577)  | 2011-11-18T00:00:00Z (xsd:dateTime)               |
| Minecraft (wd:Q49740) | Commons category (wdt:P373)  | Minecraft                                         |
| Minecraft (wd:Q49740) | copyright status (wdt:P6216) | copyrighted (wd:Q50423863)                        |
| Minecraft (wd:Q49740) | described at URL (wdt:P973)  | <https://www.minecraft.net/en-us/about-minecraft> |
| Minecraft (wd:Q49740) | collection (wdt:P195)        | Museum of Modern Art (wd:Q188740)                 |
| Minecraft (wd:Q49740) | short name (wdt:P1813)       | MC (mul)                                          |
| Minecraft (wd:Q49740) | has part(s) (wdt:P527)       | Minecraft: Java Edition (wd:Q105729297)           |
| Minecraft (wd:Q49740) | copyright license (wdt:P275) | proprietary license (wd:Q3238057)                 |
| ...                   | ...                          | ...                                               |

[Assistant] I'll execute a SPARQL query that gets all publication dates (wdt:P577) for the Wikidata item for Minecraft (wd:Q49740) and returns the maximum (most recent) date. I'll include the item IRI and its English label as well. Now I'll run the query.

[Tool]
Got 1 row and 3 columns:
| item                  | itemLabel      | mostRecentPublicationDate           |
| --------------------- | -------------- | ----------------------------------- |
| Minecraft (wd:Q49740) | Minecraft (en) | 2011-11-18T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?erratum ?label ?cleaned WHERE {
  ?erratum wdt:P31 wd:Q1348305 .
  ?erratum rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" ) FILTER ( STRSTARTS( ?label , "Erratum:" ) ) FILTER NOT EXISTS {
    ?any wdt:P2507 ?erratum
  }
  BIND( REPLACE( ?label , '^Erratum:\\s*' , '' ) AS ?cleaned ) FILTER ( STRLEN( ?cleaned ) > 20 )
}
ORDER BY ?erratum

Got 5,658 rows and 3 columns, showing the first 5 and last 5 rows below:
| erratum                                                                             | label                                                                    | cleaned                                                                  |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | ------------------------------------------------------------------------ |
| Erratum: Novel Aptamer-Functiona...m Cell Recruitment [Corrigendum] (wd:Q100298620) | Erratum: Novel Aptamer-Functiona...m Cell Recruitment [Corrigendum] (en) | Novel Aptamer-Functionalized Nan...m Cell Recruitment [Corrigendum] (en) |
| Erratum: Iron Oxide Nanoparticle...ls to Injury Sites [Corrigendum] (wd:Q100298621) | Erratum: Iron Oxide Nanoparticle...ls to Injury Sites [Corrigendum] (en) | Iron Oxide Nanoparticles Promote...ls to Injury Sites [Corrigendum] (en) |
| Erratum: Fabrication and Charact...osidase Inhibition [Corrigendum] (wd:Q100298624) | Erratum: Fabrication and Charact...osidase Inhibition [Corrigendum] (en) | Fabrication and Characterization...osidase Inhibition [Corrigendum] (en) |
| Erratum: Oral Administration of ... Toxoplasma gondii [Corrigendum] (wd:Q100298692) | Erratum: Oral Administration of ... Toxoplasma gondii [Corrigendum] (en) | Oral Administration of Encapsula... Toxoplasma gondii [Corrigendum] (en) |
| Erratum: A Predictive Model Offo...l Assessment Tools [Corrigendum] (wd:Q100298712) | Erratum: A Predictive Model Offo...l Assessment Tools [Corrigendum] (en) | A Predictive Model Offor Attenti...l Assessment Tools [Corrigendum] (en) |
| ...                                                                                | ...                                                                      | ...                                                                      |
| Erratum: Meyer, J., et al. Chang...Public Health 2020, 17(18), 6469 (wd:Q99725289)  | Erratum: Meyer, J., et al. Chang...Public Health 2020, 17(18), 6469 (en) | Meyer, J., et al. Changes in Phy...Public Health 2020, 17(18), 6469 (en) |
| Erratum: Witschen, P.M., et al. ...t Cancer. Cancers 2020, 12, 1325 (wd:Q99726039)  | Erratum: Witschen, P.M., et al. ...t Cancer. Cancers 2020, 12, 1325 (en) | Witschen, P.M., et al. Tumor Cel...t Cancer. Cancers 2020, 12, 1325 (en) |
| Erratum: Comparative ecology of ... numerical approach to modelling (wd:Q99868507)  | Erratum: Comparative ecology of ... numerical approach to modelling (en) | Comparative ecology of Quebec bo... numerical approach to modelling (en) |
| Erratum: A method for the extrac...m leaf tissue without maceration (wd:Q99868747)  | Erratum: A method for the extrac...m leaf tissue without maceration (en) | A method for the extraction of c...m leaf tissue without maceration (en) |
| Erratum: Validation of Pythium d... as Pythium delawarense sp. nov. (wd:Q99887878)  | Erratum: Validation of Pythium d... as Pythium delawarense sp. nov. (en) | Validation of Pythium delawarii as Pythium delawarense sp. nov. (en)     |

Thought process and steps performed:
1) I searched for the class/entity used for "erratum" and found wd:Q1348305 (erratum).
2) I found the property for corrigendum / erratum: P2507.
3) I wrote and executed a SPARQL query that: selects items that are instances of Q1348305, have an English rdfs:label beginning with "Erratum:", are not referenced by any item using property wdt:P2507, computes a cleaned label by removing the leading "Erratum: ", and filters to cleaned labels longer than 20 characters.

Results:
- The query (above) returns the item IRIs (?erratum), their English labels (?label) starting with "Erratum:", and the cleaned labels (?cleaned) with the leading "Erratum: " removed.
- A separate COUNT query shows there are 5,658 distinct items matching these criteria.

You can run the provided SPARQL query against the Wikidata endpoint to retrieve the full list of matching errata (item IRIs and labels).

What are the errata (published corrections to previous publications) with English labels starting with "Erratum:" that are not referenced by any item using the "corrigendum / erratum" property? Also, provide their corresponding item labels (after removing the "Erratum: " prefix) and items, where the item labels are longer than 20 characters.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the errata (published corrections to previous publications) with English labels starting with "Erratum:" that are not referenced by any item using the "corrigendum / erratum" property? Also, provide their corresponding item labels (after removing the "Erratum: " prefix) and items, where the item labels are longer than 20 characters.

[Assistant] Step 1: I'll search for the entity representing "erratum" to identify the class (instance of) used in Wikidata. I'll run an entity search for "erratum".

[Tool]
Top 10 entity alternatives:
1. erratum, also known as errata, published erratum, errata leaf, errata slip, correction slip (wd:Q1348305)
2. Erratum (wd:Q9254813): 2011 film by Marek Lechki, instance of film
3. Corrigendum to: effects of postm...y in rat and human brain tissues, also known as Erratum (wd:Q48227070): scientific article published in April 1999, instance of scholarly article, instance of erratum
4. Erratum (wd:Q58899648): instance of scholarly article, instance of erratum
5. Erratum (wd:Q58899685): scholarly article published in Mycoses, instance of scholarly article, instance of erratum
6. Erratum (wd:Q58899662): instance of scholarly article, instance of erratum
7. Erratum (wd:Q58899659): instance of scholarly article, instance of erratum
8. Erratum (wd:Q58899658): instance of scholarly article, instance of erratum
9. Erratum (wd:Q58899657): instance of scholarly article, instance of erratum
10. Erratum (wd:Q58899654): instance of scholarly article, instance of erratum

[Assistant] Next I'll search for the property "corrigendum / erratum" to get its property identifier.

[Tool]
Top 10 property alternatives:
1. corrigendum / erratum, also known as corrected by, corrigenda, corrigendum, errata, erratum (wd:P2507 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): published notice that corrects or amends a previous publication
2. page(s), also known as pp., pgs., pg., page number, pages (wd:P304 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): page number of source referenced for statement. Note "column(s)" (P3903) and "folio(s)" (P7416) for other numbering systems
3. amended by, also known as altered by, changed by, corrected by, has addendum, modified by (wd:P2567 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): document is amended by specified other document
4. stated in, also known as stated on, stated at, source of claim, originating source, in statement (wd:P248 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): to be used in the references field to refer to the information d...805; for the type of document in which a claim is made use P3865
5. place of publication, also known as country (published in), where published, release region, released in, published in (place) (wd:P291 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): geographical place of publication of the edition (use 1st edition when referring to works), subproperty of significant place
6. source of transfer, also known as from, sender, source, starting point (wd:P12693 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): entity that a transferred item is initially associated with, before this process associates it with another entity
7. source website for the property, also known as property source, Wikidata property source, website source, URL for the property, source website of the property (wd:P1896 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): URL of website acting as source of data for this Wikidata property, subproperty of URL
8. location of discovery, also known as found in, location of discovered object, findspot, place of discovery, site of discovery (wd:P189 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): where the item was located when discovered, subproperty of significant place
9. floruit, also known as fl, work period, living, known alive in, flourished (wd:P1317 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): date when the person was known to be active or alive, when birth or death not documented
10. subject named as, also known as established as, entity named as, established form, established heading, named as (wd:P1810 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): name by which a subject is recorded in a database, mentioned as a contributor of a work, or is referred to in a particular context, subproperty of name

[Assistant] I will find all items that are instances of erratum (wd:Q1348305) and have an English rdfs:label that starts with "Erratum:". Then I will check which of these are not referenced by any item using property P2507 (corrigendum / erratum). I'll search for items with labels matching that pattern.

[Tool]
Got 1,000 rows and 2 columns, showing the first 5 and last 5 rows below:
| erratum                                                                             | erratumLabel                                                             |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Erratum: Novel Aptamer-Functiona...m Cell Recruitment [Corrigendum] (wd:Q100298620) | Erratum: Novel Aptamer-Functiona...m Cell Recruitment [Corrigendum] (en) |
| Erratum: Iron Oxide Nanoparticle...ls to Injury Sites [Corrigendum] (wd:Q100298621) | Erratum: Iron Oxide Nanoparticle...ls to Injury Sites [Corrigendum] (en) |
| Erratum: Fabrication and Charact...osidase Inhibition [Corrigendum] (wd:Q100298624) | Erratum: Fabrication and Charact...osidase Inhibition [Corrigendum] (en) |
| Erratum: Oral Administration of ... Toxoplasma gondii [Corrigendum] (wd:Q100298692) | Erratum: Oral Administration of ... Toxoplasma gondii [Corrigendum] (en) |
| Erratum: A Predictive Model Offo...l Assessment Tools [Corrigendum] (wd:Q100298712) | Erratum: A Predictive Model Offo...l Assessment Tools [Corrigendum] (en) |
| ...                                                                                | ...                                                                      |
| Erratum: Changes in Dry Matter a...ation of Species-Rich Grasslands (wd:Q113066449) | Erratum: Changes in Dry Matter a...ation of Species-Rich Grasslands (en) |
| Erratum: "Restoration of four-di...rinsic Hamilton–Jacobi approach" (wd:Q113079196) | Erratum: "Restoration of four-di...rinsic Hamilton–Jacobi approach" (en) |
| Erratum: Chiral symmetry restora... Rev. D86, 034030 (2012)] (wd:Q113089676) | Erratum: Chiral symmetry restora... Rev. D86, 034030 (2012)] (en) |
| Erratum: Grand unification and p...n at low energies. Phenomenology (wd:Q113089786) | Erratum: Grand unification and p...n at low energies. Phenomenology (en) |
| Erratum: Two-neutrino double β d... Rev. C68, 064310 (2003)] (wd:Q113089841) | Erratum: Two-neutrino double β d... Rev. C68, 064310 (2003)] (en) |

[Assistant]
Now I'll run a SPARQL query that:
- finds items that are instances of erratum (wd:Q1348305),
- whose English rdfs:label starts with "Erratum:",
- are not referenced by any item via property wdt:P2507,
- computes a cleaned label by removing the "Erratum: " prefix (allowing optional spaces),
- and only returns those where the cleaned label is longer than 20 characters.

I'll execute that query to get the exact items and labels.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The target ?cleanLabel of an AS clause was already used in the query body.

[Assistant] The engine complains about using ?cleanLabel in AS when already used; I'll avoid naming collision by assigning a different variable. I'll compute cleaned label into ?clabel.

[Tool]
Got 1,000 rows and 3 columns, showing the first 5 and last 5 rows below:
| erratum                                                                             | label                                                                    | clabel                                                                   |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | ------------------------------------------------------------------------ |
| Erratum: Novel Aptamer-Functiona...m Cell Recruitment [Corrigendum] (wd:Q100298620) | Erratum: Novel Aptamer-Functiona...m Cell Recruitment [Corrigendum] (en) | Novel Aptamer-Functionalized Nan...m Cell Recruitment [Corrigendum] (en) |
| Erratum: Iron Oxide Nanoparticle...ls to Injury Sites [Corrigendum] (wd:Q100298621) | Erratum: Iron Oxide Nanoparticle...ls to Injury Sites [Corrigendum] (en) | Iron Oxide Nanoparticles Promote...ls to Injury Sites [Corrigendum] (en) |
| Erratum: Fabrication and Charact...osidase Inhibition [Corrigendum] (wd:Q100298624) | Erratum: Fabrication and Charact...osidase Inhibition [Corrigendum] (en) | Fabrication and Characterization...osidase Inhibition [Corrigendum] (en) |
| Erratum: Oral Administration of ... Toxoplasma gondii [Corrigendum] (wd:Q100298692) | Erratum: Oral Administration of ... Toxoplasma gondii [Corrigendum] (en) | Oral Administration of Encapsula... Toxoplasma gondii [Corrigendum] (en) |
| Erratum: A Predictive Model Offo...l Assessment Tools [Corrigendum] (wd:Q100298712) | Erratum: A Predictive Model Offo...l Assessment Tools [Corrigendum] (en) | A Predictive Model Offor Attenti...l Assessment Tools [Corrigendum] (en) |
| ...                                                                                | ...                                                                      | ...                                                                      |
| Erratum: "Time Schedule and Prog...: TV News in Norway and Denmark" (wd:Q128011498) | Erratum: "Time Schedule and Prog...: TV News in Norway and Denmark" (en) | "Time Schedule and Program Profile: TV News in Norway and Denmark" (en)  |
| Erratum: Light scattering from e...ctuations in magnetic insulators (wd:Q128011515) | Erratum: Light scattering from e...ctuations in magnetic insulators (en) | Light scattering from energy fluctuations in magnetic insulators (en)    |
| Erratum: Bremsstrahlung in High Energy Nucleon-Nucleon Collisions (wd:Q128011587)   | Erratum: Bremsstrahlung in High Energy Nucleon-Nucleon Collisions (en)   | Bremsstrahlung in High Energy Nucleon-Nucleon Collisions (en)            |
| Erratum: Yu, W.; Jiao, J. Sustai...r. Sustainability 2018, 10, 2287 (wd:Q128020632) | Erratum: Yu, W.; Jiao, J. Sustai...r. Sustainability 2018, 10, 2287 (en) | Yu, W.; Jiao, J. Sustainability ...r. Sustainability 2018, 10, 2287 (en) |
| Erratum: Patience, Matthew: Acqu...Speakers. Languages 3 (2018): 42 (wd:Q128056528) | Erratum: Patience, Matthew: Acqu...Speakers. Languages 3 (2018): 42 (en) | Patience, Matthew: Acquisition o...Speakers. Languages 3 (2018): 42 (en) |

[Assistant]
The query returned many results. I must ensure the query returns the IRIs of items (it does), their English label, and the cleaned label. The user also asked to "provide their corresponding item labels (after removing the 'Erratum: ' prefix) and items, where the item labels are longer than 20 characters." I interpreted that as selecting errata with cleaned labels longer than 20 characters. I should confirm that none of these errata are referenced by any item using property P2507; we used FILTER NOT EXISTS for that.

I'll now finalize by returning the SPARQL query and the answer summarizing the results. But per the Additional rules, I must explain thought process before and after each step and function call. I have been doing that. I must also ensure final SPARQL query executed — yes. Now prepare the final answer, including the SPARQL query and a brief summary of results (maybe list count). I should include the query used.

I should get the count of results to report how many items match. I'll run a COUNT query to get number of results.

[Tool]
Got 1 row and 1 column:
| count          |
| -------------- |
| 5658 (xsd:int) |

[Tool] Stopped generation process